Web content illustrated with images or videos often draw the attention of the reader. For example, users may be more engaged with the content of an article displayed as images, resulting in more views of that article, and consumers are more likely to consider or contact a business when an image that accompanies the local search results allows a consumer to more readily determine that a particular search result is more relevant for the consumer's purposes. Moreover, in many scenarios, a user can absorb information more quickly when that information is presented using a combination of text and graphical communication. For instance, an article presented with an appropriate number of relevant images may be comprehended more efficiently and may hold a reader's attention more effectively than a similar article without images.
Websites can include hundreds of webpages containing articles or other text content that would benefit from suitable images or other graphical media assets. A user, such as a marketer or website manager, may be unable to review each webpage to determine whether graphical media assets are helpful and, if so, what type of assets are appropriate for the text content contained on the webpage. In addition, repositories of available and allowed media assets may contain thousands of media assets, each asset having technical characteristics (e.g., an asset type, a size, a resolution) and content characteristics (e.g., a depicted image, a license for use, appropriateness for an age bracket, etc.). A digital repository may be updated frequently, as groups of assets are automatically introduced or removed. Familiarizing a user with all available assets to determine which particular one is suitable for a given text item may therefore be infeasible or impractical. Moreover, there may be multiple images that are relevant to a text content item, which makes the process of manually choosing the most appropriate images a tedious process.
Prior solutions for modifying web pages and other electronic content to include selected media assets may present disadvantages. For instance, in certain cases, individual sentences in a web page or other electronic content may be analyzed to identify media assets that correspond to the content of those sentences. But focusing on individual sentences for can provide sub-optimal results for selecting appropriate media assets to include with the web page or other electronic content. In one example, focusing on individual sentences may overlook contextual information that is conveyed by a set of sentences when considered together. In another example, selecting a media asset for each analyzed sentence may cause too many assets to be selected, especially for text content such as long and complicated online articles. In these examples, or other cases where media assets are selected without considering sets of sentences in combination, selecting media assets to accompany text in a web page or other electronic content will utilize computing resources expended on the selection process without enhancing a user's engagement with the web page or other electronic content.
Therefore, it is desirable to provide methods and systems to quickly and accurately analyze text in a content item and to select relevant media assets for an appropriate number of sentences in the text content.